Head of Data Science - Fraud Insights

Bring the rigor of an applied economist to fraud - proper identification strategies, causal inference, and natural experiments. Design studies and analytical frameworks that produce findings you can stand behind publicly. Answer questions like: What drove the surge in synthetic identity fraud post-CARES Act? How do adversarial networks respond to model updates? What are the second-order effects of regulatory changes on fraud displacement across verticals?, Serve as the connective tissue between external signals - regulatory guidance, legislative changes, CFPB and FinCEN trends, macroeconomic shifts that alter fraud incentives, emerging typologies from industry consortia - and Socure's internal research, modeling, and product roadmaps. When a new regulation drops or a fraud pattern surfaces in the press, you already have the data story and the analysis ready., Build tight feedback loops with Socure's modeling, product, and engineering organizations so that what you learn in the data becomes new signals, smarter models, better products, and stronger go-to-market positioning. You will have a direct line into the strategic roadmap and report directly to the Chief AI & Innovation Officer., * Research Depth & Econometric Rigor. You approach fraud data the way a serious economist approaches a policy question - with proper identification strategies, an appreciation for confounding, a healthy skepticism of naive correlations, and the discipline to distinguish causation from coincidence. Comfortable with panel data methods, diff-in-diff, regression discontinuity, survival analysis, network econometrics, and the full toolkit of applied causal inference.

• Deep Fraud Domain Expertise. You've spent meaningful time in the trenches - synthetic identity, first-party fraud, account takeover, bust-out rings, AML-adjacent typologies, mule networks, or related domains. You understand the adversarial game theory at play and respect the sophistication of the actors on the other side.
• Data Fluency at Scale. You've worked with large-scale identity, behavioral, or transaction datasets. You understand graph structures, feature engineering at the identity level, and the operational realities of productionizing insights. Conversant in Python, SQL, graph analytics, and ML frameworks.
• External Credibility & Presence. You have a track record of representing an organization publicly and credibly - major conference appearances, regulatory working groups, authored research the market takes seriously, or a reputation that precedes you in the fraud and identity space.
• Executive Communication Without Dumbing It Down. You can write a 2-page brief for a CEO that captures all the important nuance, and go 10 levels deep with a PhD data scientist without losing them. You know the difference between simplifying and falsifying, and you never do the latter.
• Regulatory & Macro-Intelligence Fluency. You follow the regulatory environment - CFPB rulemaking, FinCEN guidance, state-level identity legislation, open banking frameworks - and understand how policy changes alter fraud incentives and attack surfaces.

Do you have experience in Team leadership?, * Advanced degree (MS or PhD strongly preferred) in Economics, Statistics, Econometrics, Applied Mathematics, Computer Science, or a related quantitative field

• 10+ years of applied experience in data science, fraud analytics, risk research, or quantitative economics, with demonstrable impact at scale
• Proven expertise in fraud, identity risk, financial crime, or adjacent domains
• Strong command of causal inference, statistical modeling, and modern ML/AI techniques applied to adversarial or risk problems
• Track record of external thought leadership - publications, conference presentations, regulatory engagement, or equivalent market-facing credibility
• Exceptional written and verbal communication skills; ability to author compelling, rigorous, market-facing research
• Experience leading and developing high-performing technical teams, * Experience with graph-based analytics, identity network modeling, or fraud ring detection using Neo4j, AWS Neptune, or custom graph frameworks
• Familiarity with the regulatory landscape governing identity verification, fraud prevention, and consumer financial protection (CFPB, FinCEN, OCC, state AGs)
• Experience with device intelligence, behavioral biometrics, email/phone/IP signals, or browser fingerprinting in a fraud context
• Published research or white papers in peer-reviewed journals, industry publications, or prominent market forums
• Experience working in or alongside financial services, fintech, credit bureaus, payments networks, or fraud consortia
• Exposure to explainable AI, model governance, or adverse action frameworks relevant to consumer-facing decisioning

Reports to: Chief AI & Innovation Officer

Socure is building the identity trust infrastructure for the digital economy - verifying 100% of good identities in real time and stopping fraud before it starts. The mission is big, the problems are complex, and the impact is felt by businesses, governments, and millions of people every day. We hire people who want that level of responsibility. People who move fast, think critically, act like owners, and care deeply about solving customer problems with precision. If you want predictability or narrow scope, this won't be your place. If you want to help build the future of identity with a team that holds a high bar for itself - keep reading., Socure sits on one of the most consequential datasets in the world - a global identity graph spanning hundreds of millions of identities, incorporating PII, device signals, behavioral telemetry, network relationships, and a continuous feedback loop of real-world fraud and verification outcomes across thousands of clients. The patterns inside this graph tell the story of how fraud evolves: who the adversaries are, how they adapt, and where they're going next. We are not looking for someone to report what happened. We are looking for someone who can explain why it happened, predict what comes next, and make that story impossible to ignore - for regulators, customers, boards, and the market. This person will sit directly at the intersection of rigorous research, macroeconomic and regulatory intelligence, and the richest identity dataset in the industry.